// Copyright (c) 2020, Huawei Technologies.All rights reserved.
//
// Licensed under the BSD 3-Clause License  (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "torch_npu/csrc/framework/utils/OpAdapter.h"
#include "torch_npu/csrc/aten/NPUNativeFunctions.h"

namespace at_npu {
namespace native {

at::Tensor& softshrink_out_nocheck(
    const at::Tensor& self,
    at::Scalar lambd,
    at::Tensor& result) {

  OpPreparation::CheckMemory({self}, {result});
  OpCommand cmd;
  cmd.Name("SoftShrink")
      .Input(self)
      .Output(result)
      .Attr("lambd", lambd)
      .Run();
      
  return result;
}

at::Tensor& NPUNativeFunctions::softshrink_out(
    const at::Tensor& self,
    at::Scalar lambd,
    at::Tensor& result) {
  TORCH_CHECK(lambd.toFloat() > 0, "lambd should be greater than 0");
  OpPreparation::CheckOut(
      {self},
      result,
      self);
  
  if (!NpuUtils::check_match(&result)) {
    at::Tensor contiguousResult = NpuUtils::format_contiguous(result);
    softshrink_out_nocheck(self, lambd, contiguousResult);
    NpuUtils::format_fresh_view(result, contiguousResult);
  } else {
    softshrink_out_nocheck(self, lambd, result);
  }

  return result;
}

at::Tensor NPUNativeFunctions::softshrink(const at::Tensor& self, at::Scalar lambd) {
  TORCH_CHECK(lambd.toFloat() > 0, "lambd should be greater than 0");
  at::Tensor result = OpPreparation::ApplyTensor(self);

  softshrink_out_nocheck(self, lambd, result);
  
  return result;
}
} // namespace native
} // namespace at_npu
